def __init__(
self,
*,
workflow_id: str,
execution_id: str,
location: str,
project_id: str,
success_states: Optional[Set[Execution.State]] = None,
failure_states: Optional[Set[Execution.State]] = None,
retry: Optional[Retry] = None,
request_timeout: Optional[float] = None,
metadata: Sequence[Tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: Optional[Union[str, Sequence[str]]] = None,
**kwargs,
):
super().__init__(**kwargs)
self.success_states = success_states or {
Execution.State(Execution.State.SUCCEEDED)
}
self.failure_states = failure_states or {
Execution.State(Execution.State.FAILED),
Execution.State(Execution.State.CANCELLED),
}
self.workflow_id = workflow_id
self.execution_id = execution_id
self.location = location
self.project_id = project_id
self.retry = retry
self.request_timeout = request_timeout
self.metadata = metadata
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
def execute(self, context: 'Context'):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
self.log.info("Creating execution")
execution = hook.create_execution(
workflow_id=self.workflow_id,
execution=self.execution,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
execution_id = execution.name.split("/")[-1]
self.xcom_push(context, key="execution_id", value=execution_id)
WorkflowsExecutionLink.persist(
context=context,
task_instance=self,
location_id=self.location,
workflow_id=self.workflow_id,
execution_id=execution_id,
project_id=self.project_id or hook.project_id,
)
return Execution.to_dict(execution)
def execute(self, context: 'Context'):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
self.log.info("Retrieving execution %s for workflow %s", self.execution_id, self.workflow_id)
execution = hook.get_execution(
workflow_id=self.workflow_id,
execution_id=self.execution_id,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
return Execution.to_dict(execution)
def execute(self, context: 'Context'):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
self.log.info("Retrieving executions for workflow %s", self.workflow_id)
execution_iter = hook.list_executions(
workflow_id=self.workflow_id,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
return [Execution.to_dict(e) for e in execution_iter if e.start_time > self.start_date_filter]
def execute(self, context: 'Context'):
hook = WorkflowsHook(gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain)
self.log.info("Canceling execution %s", self.execution_id)
execution = hook.cancel_execution(
workflow_id=self.workflow_id,
execution_id=self.execution_id,
location=self.location,
project_id=self.project_id,
retry=self.retry,
timeout=self.timeout,
metadata=self.metadata,
)
WorkflowsExecutionLink.persist(
context=context,
task_instance=self,
location_id=self.location,
workflow_id=self.workflow_id,
execution_id=self.execution_id,
project_id=self.project_id or hook.project_id,
)
return Execution.to_dict(execution)